Confusion matrix of the CANet presenting the probability of an expression in the row to be classified as an expression in the column with the first test approach in the JAFFE database (SU: surprise, HA: happiness, AN: anger, DI: disgust, SA: sadness, NE: neutral, FE: fear).

<p>Confusion matrix of the CANet presenting the probability of an expression in the row to be classified as an expression in the column with the first test approach in the JAFFE database (SU: surprise, HA: happiness, AN: anger, DI: disgust, SA: sadness, NE: neutral, FE: fear).</p><p>Confusion matrix of the CANet presenting the probability of an expression in the row to be classified as an expression in the column with the first test approach in the JAFFE database (SU: surprise, HA: happiness, AN: anger, DI: disgust, SA: sadness, NE: neutral, FE: fear).</p

Comparison between the facial expression recognition rate (%) obtained by CANet and different methods without feature extraction with the second test approach in the JAFFE database.

<p>Comparison between the facial expression recognition rate (%) obtained by CANet and different methods without feature extraction with the second test approach in the JAFFE database.</p><p>Comparison between the facial expression recognition rate (%) obtained by CANet and different methods without feature extraction with the second test approach in the JAFFE database.</p

Multi-class recognition system of the CANet.

<p>Multi-class recognition system of the CANet.</p

CANet architecture composed of 2-D layers in a bottleneck shape for image autoassociation:

<p>(a) network layers in which neurons are connected to receptive fields with different sizes in the input and output layers; (b) connectivity model of a neuron in the constructive layer.</p

CANet training model for a set of training images from the class .

<p>CANet- is the output of the model.</p

JAFFE images after pre-processing.

<p>JAFFE images after pre-processing.</p

CANet pruning algorithm.

<p>The mean error rates are sorted and the neurons associated with the lowest rates are kept in the reconstruction layer.</p

Quadtree model of the receptive fields hierarchy.

<p>Initially, there is only one receptive field with the same height and width of the output layer, given by and , respectively. The receptive field is divided into four receptive fields with sizes and . Finally, the receptive field denoted by is divided into four receptive fields with sizes and .</p

Algorithm 1: Pseudocode of the constructive-prunning algorithm.

<p>Algorithm 1: Pseudocode of the constructive-prunning algorithm.</p><p>Algorithm 1: Pseudocode of the constructive-prunning algorithm.</p

Notations and definitions used to describe the CANet.

<p>Notation and definitions used to describe the CANet.</p><p>Notations and definitions used to describe the CANet.</p